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Springer (part of Springer Nature), Evolutionary Ecology, 5(26), p. 1085-1099

DOI: 10.1007/s10682-012-9593-z

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Meta-analytic insights into evolutionary ecology: An introduction and synthesis

Journal article published in 2012 by Shinichi Nakagawa ORCID, Robert Poulin
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Meta-analysis now pervades ecology and evolutionary biology as the tool of choice for the synthesis of primary results. In the opening article of this special issue on "Meta-analytic insights into evolutionary ecology", we begin by contrasting meta-analysis with the more traditional 'narrative' reviewing approach. Although it is not without faults, we find that meta-analysis usually outperforms qualitative reviews with respect to testing hypotheses, identifying sources of heterogeneity among primary results, assessing publication bias, and even generating new hypotheses and future research directions. We then highlight the key messages of the nine other contributions to this special issue, on the topics of natural selection, sexual selection, community ecology, host-parasite interactions, plant evolutionary ecology, social behaviour, behavioural syndromes, conservation biology, and methodological advances. We also discuss issues associated with the quality assessments and the inadequate reporting of basic statistics in primary empirical studies, and the need to share credit with the authors of those primary studies through actual citations. Finally, we turn to the future and argue that meta-analysis needs to adopt the principles of systematic reviews, following strict protocols that facilitate replicable and updatable research syntheses. Ecology and evolutionary biology urgently need collaborative networks such as the Cochrane Collaboration in the medical sciences, to oversee the standards of systematic reviews and meta-analyses. The formation of a collaborative meta-analytic research network will be an important step for meta-analysis to solidify its central role in research and data synthesis.